Research Software Developer

UNC-Chapel Hill•Chapel Hill, NC

About The Position

The Senior Research Software Engineer will support research imaging data preprocessing, image processing, implement data cleaning, train research team on image analysis using Python, FSL, SPM, Freesurfer, and other platforms. The incumbent will further support the software and hardware environments for successful implementation of the planned image analyses, collaborate with other national labs to align our site capacity with multi-site projects of which we are a part. The Senior Research Software Engineer will serve as a highly specialized technical leader responsible for architecting, developing, and optimizing advanced computational systems that support large-scale neuroimaging research. This position plays a critical role in enabling cutting-edge scientific discovery through the design and implementation of scalable, reproducible data pipelines and analytical frameworks for complex MRI, MRS, PET datasets. Operating at the intersection of neuroscience, data science, and software engineering, this role drives innovation in neuroinformatics infrastructure, including the integration of data management platforms, high-performance computing environments, and advanced statistical methodologies. They will collaborate closely with faculty investigators, clinicians, and interdisciplinary research teams to translate complex research questions into robust computational solutions and actionable scientific insights. Key contributions include leading the development of automated processing pipelines, advancing methodological approaches in neuroimaging analytics, and creating sophisticated visualization tools that effectively communicate complex findings. The role requires deep domain expertise in neuroanatomy, scientific programming, and neuroimaging ecosystems, as well as a strong commitment to reproducibility.

Requirements

Significant experience developing scientific software and computational workflows.
Programming in Python, R, or other scientific computing environments.
Experience with neuroimaging tools such as FreeSurfer, FSL, AFNI, or related frameworks.
Experience working with neuroimaging or other large biomedical datasets.
Familiarity with neuroinformatics platforms, including research data systems such as XNAT or REDCap.
Experience collaborating with interdisciplinary research teams.
Demonstrated contributions to research software, analysis tools, or data processing pipelines.
Demonstrated ability to adhere to HIPAA.
Ability to produce scientific reports, memos, and publications for peer-reviewed journals and grant writing and submission.

Nice To Haves

Development of automated pipelines for large-scale data processing deployable on cluster such as SLURM.
Experience working with DICOM data and imaging data anonymization workflows.
Data visualization for scientific analysis and reporting.
Use of version control systems (e.g., Git) and collaborative software development practices.
Experience working in Linux or research computing environments.

Responsibilities

Support research imaging data preprocessing and image processing.
Implement data cleaning.
Train research team on image analysis using Python, FSL, SPM, Freesurfer, and other platforms.
Support the software and hardware environments for successful implementation of planned image analyses.
Collaborate with other national labs to align site capacity with multi-site projects.
Architect, develop, and optimize advanced computational systems for large-scale neuroimaging research.
Design and implement scalable, reproducible data pipelines and analytical frameworks for complex MRI, MRS, PET datasets.
Drive innovation in neuroinformatics infrastructure, including integration of data management platforms, high-performance computing environments, and advanced statistical methodologies.
Collaborate with faculty investigators, clinicians, and interdisciplinary research teams to translate research questions into computational solutions.
Lead the development of automated processing pipelines.
Advance methodological approaches in neuroimaging analytics.
Create sophisticated visualization tools to communicate complex findings.